A Sociological Analysis of Structural Racism in Student List Products


    Ozan Jaquette

    UCLA

    Karina Salazar

    University of Arizona

    ozanj.github.io/student_list_hsls/slides/student_list.html

      Introduction


        The market for college access


        A two-sided matching problem in which market allocates students to colleges (Hoxby, 1997; Hoxby, 2009)

        • Barriers to efficient market:
          • transportation costs; information costs
        • Students
          • Goal: want to attend college
          • Information problem: Don’t know where they will be admitted, how much it will cost
        • Colleges want to enroll students
          • Enrollment goals: academic profile; revenue; diversity; internal constituents
          • Information problem: Don’t know who/where the “good” students are, how to contact them

        Matchmaking

        • “Inquiries” (student as first contact)
        • Students send test scores or fill out inquiry form
        • The enrollment problem
          • Most colleges cannot survive/thrive solely from students who reach out on their own
          • Must find desirable prospects who can be convinced to apply/enroll

          Student lists products


          “Student list” products are a matchmaking intermediary that connects colleges to prospects

          • Third-party vendors obtain data and contact info about prospecs (e.g., Testing orgs, search engines)
          • Vendors sell contact information of prospects to colleges looking for students
            • Colleges choose prospect profiles by filtering on search filters (e.g., zip code, test score)

          Policy concerns about student list products

          • Problem with underlying products
            • Search filters incorporate “racialized inputs” (Norris, 2021) that systematically disadvantage underrepresented students of color
          • Problem with utilization of products
            • University administrators may choose combinations of search filters that result in racial exclusion

          Research questions

          1. What is relationship between search filters and racial composition of included vs excluded students?
          2. How do public universities use racialized search filters in concert with other search filters when purchasing student lists?
          3. What is observed racial composition of student list purchases that utilize racialized search filters in concert with other search filters?

            Research overview


            Research questions


            1. What is relationship between search filters and racial composition of included vs excluded students?
              • Reconstruct College Board student list product using nationally representative sample of 9th graders from 2009 (NCES High School Longitudinal Survey)
              • Simulate which students are included versus excluded when certain search filters are utilized

            1. How do public universities use racialized search filters in concert with other search filters when purchasing student lists?
              • Analyze 830 student lists purchased by 14 public universities, collected via public records requests

            1. What is observed racial composition of student list purchases that utilize racialized search filters in concert with other search filters?
              • Analyze targeted student list purchases, where we obtained both the order details and deidentified prospect-level data

              Literature Review


                Scholarship on recruiting from sociology


                Enrollment funnel: prospects >> leads >> inquires >> applicants >> admits >> enrolled

                • Most scholarship on enrollment management focuses on latter stages (admissions, financial aid)
                • Body of research in sociology that analyzes recruiting “in the wild”

                Recruiting from perspective of high school students (Holland, 2019)
                • Underrepresented students sensitive to feeling “wanted” by colleges

                Connections between high schools and colleges from organizational behavior perspective
                • Off-campus recruiting visits indicate a network tie and enrollment priorities
                • recruiting from perspective of private college (Stevens, 2007), private HS counselors (Khan, 2011)
                • Recruiting visits by public research univs (e.g., Salazar, Jaquette, and Han, 2021; and Salazar, 2022)

                Recruiting at open-access PSIs for adults (e.g., and Cottom, 2017; and Posecznick, 2017)
                • For-profits have demand in Black/Latinx communities because traditional colleges ignore them

                Scholarship assumes that recruiting is something done wholly done by individual colleges
                • Third-party products and vendors structure recruiting behavior by colleges
                • How do products incorporate structural inequality? How are they utilized by colleges?

                  Background


                    Where do student lists fit in recruiting


                    Prospects

                    • Population of desirable potential students

                    Leads

                    • Prospects whose contact info has been obtained

                    Inquiries

                    • Prospects who have contacted the institution
                      • Institution as first contact (leads)
                      • Student as first contact

                    Interventions along the funnel
                    • Convert prospects to leads
                      • purchase student lists
                    • Convert leads/inquiries to applicants
                      • Email, mail, targeted social media
                    • Convert admits to enrolles
                      • Financial aid packages
                    **The enrollment funnel**

                    Enrollment Funnel

                    Source: pngwing.com

                      College Board and ACT student list products


                      Sources of student list data

                      • Test takers (e.g., PSAT, SAT, AP), pre-test questionnaire (demographics, preferences)
                      • More recently, from college search engines (e.g., College Board Big Future)
                      • Students can opt in or out

                      What information does a list contain ([College Board template](https://drive.google.com/file/d/1Qvc_QRi9izEF1W78Lh4nNi5NsXjCZqUE))
                      • Contact, demographic, college preferences, limited academic achievement

                      Pricing
                      • Historically, price-per-prospect (e.g., $0.50 per name); now a subscription model

                      Buying lists: “search filters” control which prospects included in purchase

                      • Commonly used search filters (Link to ACT filters)
                        • e.g., HS GPA, test score range, gender, race, geography (e.g., state), enrollment probability
                      • Salazar, Jaquette, and Han (2022) categorizes College Board search filters into four buckets:
                        • Geographic
                        • Academic
                        • Demographic
                        • Student preferences

                        Filters used in 830 lists purchased by 14 public universities


                        plot of chunk orders-filters-combined

                          College Board Search and student outcomes


                          Howell, Hurwitz, Mabel et al. (2021)

                          plot of chunk cb-fig
                          also see: Smith, Howell, and Hurwitz (2022) for effect of university purchasing profile on college choice

                            Conceptual Framework


                              Sociology of race


                              Selection devices allocate individuals to categories based on input factors (Hirschman and Bosk, 2020)

                              • Discretionary selection devices
                                • Decisions incorporate judgment of individual evaluators (e.g., holistic admissions)
                              • Standardized selection devices
                                • decisions based on mathematical function in which input values determine outcome value
                                • “actuarial” selection devices predict outcomes based on analysis of past cases
                              • Student list products are discretionary selection devices
                                • administrator chooses prospects by selecting search filters (inputs)
                                • inputs factors include descriptive characteristics and predictive analytics

                              Selection devices and racial inequality
                              • Standardized selection devices
                                • May reduce racial inequality if source of inequality is bias from individual decision-maker
                                • Do not reduce inequality due to structural racism (Bonilla-Silva, 1997)
                                  • “colorblind” selection devices reproduce inequality by utilizing inputs related to race
                              • Discretionary selection devices
                                • Sensitive to bias from decision-makers and inputs related to race

                                Racialized inputs


                                Structural racism (Tiako, South, and Ray, 2021, p. 1143)

                                • “systematic racial bias embedded in the ‘normal’ functions of laws and social relations,” whereby processes viewed as neutral or common-sense systematically disadvantage marginalized groups

                                Racialized inputs (Norris, 2021)
                                • Inputs that are “theoretically and empirically correlated with historical racial disadvantage” (p. 5)
                                • reconstructs inputs used by Moody’s city government credit rating algorithm

                                Geography inputs
                                • US racially segregated due to historic and current laws/policies/practices
                                • Zip code an input in algorithm that predicts crime recidivism (O’Neil, 2016; Benjamin, 2019)
                                  • Zip code a search filter on CB/ACT student list products
                                • Geodemographic classifications classify localities by consumer behavior (Leyshon and Thrift, 1999)
                                  • CB Geodemographic filters classify census tracts by past college enrollment (College Board, 2011)

                                Inputs based on predictive analytics
                                • Analyze determinants of an outcome in past cases, use results as an input to select future cases (e.g., ACT probability of enrollment filter)

                                  RQ1: relationship between filters and racial composition


                                  Standardized college entrance exams and AP exams as racialized inputs

                                  • Differences in test-taking and scores by race a function of historic/contemporary school segregation, differences in school funding and access to curricula (e.g., Reardon, Kalogrides, and Shores, 2019; Rodriguez and Hernandez-Hamed, 2020)
                                  • Concerns about bias in question items (e.g., and Freedle, 2003; Santelices and Wilson, 2010)

                                  P1: The condition of taking standardized assessments is associated with racial disparities in who is included versus excluded in student list products.


                                  P2: As test score threshold increases, the proportion of underrepresented minority students included in student lists declines relative to the proportion who are excluded.


                                  P3. As purchases filter on more affluent geographic localities (e.g., zip codes), the proportion of underrepresented minority students included in student lists declines relative to the proportion who are excluded.


                                  Filtering on multiple racialized inputs has compounding effect on racial inequality

                                    Methods


                                      Data


                                        HSLS09 & Student List Project


                                        High School Longitudinal Study of 2009 (HSLS09)

                                        • Unweighted analysis sample (n=16,530)
                                        • Includes students who completed 2012/2013 survey follow-ups and obtained high school transcript data
                                        • Weighted analysis sample represent approximately 4.2 million U.S. 9th graders in 2009

                                        Student List Project

                                        • Issued public records requests for student list data (2016-2020) to all public universities in four states (CA, IL, MN, TX)
                                        • Target student list vendors: College Board, ACT
                                        • For each purchased list, sought two pieces of data
                                          • “Order summary” specifying search filter criteria (LINK)
                                          • De-identified prospect-level student list (LINK)

                                          Summary of data received


                                          State# received order summary# no order summary# received list# no list# received both# did not receive both
                                          CA 9 23 13 19 9 23
                                          IL 9 3 9 3 8 4
                                          TX 15 20 16 19 10 25

                                            Orders and prospects purchased


                                            plot of chunk orders-prospects-purchased

                                              Research design


                                                Variables & Analyses


                                                RQ1: What is the relationship between student list search filters and the racial composition of students who are included versus excluded from College Board student list purchases?


                                                RQ2:


                                                • Dependent Variable: student race/ethnicity
                                                • Independent Variables: measures of student list academic and geographic filters
                                                  • Dichotomous measures of SAT, PSAT, AP completion
                                                  • Threshold measures of highest SAT, PSAT, AP scores, and GPA
                                                  • Economic measures of students’ zipcode, county, CBSA from ACS
                                                • Analyses: descriptive statistics
                                                  • All analyses compare the racial composition of included versus excluded prospects when particular filters and/or filter thresholds are utilized to purchase prospect profiles

                                                  Results


                                                    RQ1


                                                      Test Takers


                                                      P1: Racial disparities in test-taking

                                                      Enrollment Funnel
                                                      Snow
                                                      Forest
                                                      Snow
                                                      Forest

                                                        Test thresholds


                                                        P2: SAT, PSAT score thresholds and racial composition

                                                        Enrollment Funnel
                                                        P2SAT_inc
                                                        P2SAT_exc
                                                        P2PSAT_inc
                                                        P2PSAT_exc

                                                          Test thresholds


                                                          P2: AP sScore thresholds and racial composition

                                                          Enrollment Funnel
                                                          P2AP_inc
                                                          P2AP_exc
                                                          P2APstem_inc
                                                          P2APstem_exc

                                                            Geography


                                                            P3: Zip code affluence and racial composition

                                                            Enrollment Funnel
                                                            P3zip_inc
                                                            P3zip_exc

                                                              Geography


                                                              Zip vs county, affluence percentiles within CBSA

                                                              Enrollment Funnel

                                                                Academic & Geographic


                                                                GPA (3.0+) and SAT or PSAT (across score thresholds)

                                                                Enrollment Funnel
                                                                combo1_sat
                                                                combo1_psat

                                                                  Academic & Geographic


                                                                  GPA (3.0+), PSAT (150+) or SAT (1050+), and Zip (across income thresholds)

                                                                  Enrollment Funnel
                                                                  combo2_sat
                                                                  combo2_psat

                                                                    Academic & Geographic


                                                                    GPA (3.0+) and AP (across score thresholds)

                                                                    Enrollment Funnel
                                                                    combo3_ap
                                                                    combo3_apstem

                                                                      RQ2


                                                                        Broad patterns


                                                                        Filters used in order purchases

                                                                        plot of chunk orders-filters

                                                                          Combination of filters


                                                                          Filter combos used in order purchases

                                                                          ResearchMA/doctoral
                                                                          FiltersCountPercentFiltersCountPercent
                                                                          HS grad class, GPA, SAT, PSAT, Rank, State, Race 39 10% HS grad class, GPA, SAT, Zip code 206 45%
                                                                          HS grad class, PSAT, State 27 7% HS grad class, GPA, PSAT, Zip code 145 32%
                                                                          HS grad class, GPA, PSAT, State, Race 20 5% HS grad class, SAT, State 31 7%
                                                                          HS grad class, PSAT, State, Low SES 20 5% HS grad class, GPA, SAT, PSAT, Zip code 28 6%
                                                                          HS grad class, GPA, PSAT, State 17 5% HS grad class, GPA, SAT, State 7 2%
                                                                          HS grad class, GPA, SAT, State 16 4% HS grad class, SAT, Geomarket 6 1%
                                                                          HS grad class, GPA, AP score, Geomarket 15 4% HS grad class, GPA, SAT, County 5 1%
                                                                          HS grad class, GPA, SAT, PSAT, State, Segment, Gender 13 3% HS grad class, GPA, SAT, PSAT, County 4 1%
                                                                          HS grad class, PSAT, Geomarket 12 3% HS grad class, GPA, PSAT, State 2 0%
                                                                          HS grad class, SAT, State, Low SES, College size 11 3% HS grad class, SAT, Geomarket, College type 2 0%

                                                                            RQ3


                                                                              Characteristics by filters


                                                                              Prospect characteristics across individual filter criteria

                                                                              AcademicGeographicDemographic
                                                                              All domesticGPAPSATSATHS rankAP scoreZip codeStateGeomarketSegmentCBSARaceGender
                                                                              Total 3,547,620 1,101,266 1,812,447 971,237 146,660 75,479 165,924 1,173,678 1,056,951 186,519 146,313 279,626 39,546
                                                                              Location
                                                                              % In-state 38 62 30 54 83 42 98 48 17 15 4 59 6
                                                                              % Out-of-state 62 38 70 46 17 58 2 52 83 85 96 41 94
                                                                              Race/ethnicity
                                                                              % White 48 45 50 47 51 17 43 42 57 51 53 25 47
                                                                              % Asian 16 15 17 15 10 7 13 18 13 27 28 5 38
                                                                              % Black 5 7 4 7 8 17 8 5 4 3 2 11 1
                                                                              % Latinx 21 24 19 22 23 46 27 24 16 11 8 46 6
                                                                              % AI/AN 1 1 1 0 1 1 1 1 0 0 0 2 0
                                                                              % NH/PI 0 0 0 0 0 1 0 0 0 0 0 0 0
                                                                              % Multiracial 5 5 5 5 5 10 4 6 5 5 5 9 5
                                                                              % Other 0 0 0 0 0 0 0 0 0 0 0 0 0
                                                                              % No response 4 3 3 3 2 1 4 3 4 3 3 2 3
                                                                              % Missing 0 0 1 0 0 0 1 1 1 0 0 0 0
                                                                              Gender
                                                                              % Male 34 19 37 18 0 3 46 24 48 6 0 11 0
                                                                              % Female 36 23 40 20 1 15 54 27 52 9 0 12 33
                                                                              % Other 0 0 0 0 0 0 0 0 0 0 0 0 0
                                                                              % Missing 30 58 22 63 99 82 0 49 0 85 1 77 67
                                                                              Household income
                                                                              Median income $107K $105K $108K $105K $99K $90K $97K $105K $107K $130K $135K $94K $127K
                                                                              Locale
                                                                              % City 27 27 27 26 26 31 31 30 23 24 22 29 26
                                                                              % Suburban 44 47 44 48 53 40 42 42 46 54 57 47 49
                                                                              % Rural - Fringe 22 20 22 20 15 23 19 22 23 19 19 19 23
                                                                              % Rural - Distant 6 6 5 6 6 5 7 6 6 2 1 6 2
                                                                              % Rural - Remote 1 0 1 0 0 0 1 1 1 0 0 0 0
                                                                              % Missing 0 0 0 0 0 0 0 0 0 0 0 0 0

                                                                                Geodemographic segment filters


                                                                                Filter by neighborhood segments

                                                                                2011 D+ ClusterSAT MathSAT CRGoing Out of StatePercent NonWhiteNeed Financial AidMed Income
                                                                                51 546.00 533.00 32% 30% 57% $95,432
                                                                                52 480.00 470.00 30% 58% 71% $63,578
                                                                                53 561.00 544.00 32% 50% 55% $92,581
                                                                                54 458.00 443.00 25% 83% 76% $38,977
                                                                                55 566.00 565.00 52% 24% 63% $71,576
                                                                                56 420.00 411.00 29% 93% 66% $35,308
                                                                                57 541.00 519.00 52% 47% 43% $67,394
                                                                                58 533.00 489.00 28% 87% 69% $68,213
                                                                                59 561.00 562.00 52% 24% 74% $54,750
                                                                                60 589.00 590.00 63% 37% 36% $104,174
                                                                                61 585.00 567.00 51% 30% 40% $123,858
                                                                                62 596.00 595.00 67% 24% 72% $59,824
                                                                                63 548.00 541.00 39% 23% 65% $69,347
                                                                                64 466.00 466.00 48% 34% 29% $49,829
                                                                                65 440.00 433.00 23% 93% 78% $45,081
                                                                                66 499.00 492.00 20% 12% 76% $50,453
                                                                                67 519.00 501.00 27% 53% 59% $60,960
                                                                                68 552.00 558.00 52% 35% 65% $57,902
                                                                                69 534.00 521.00 37% 19% 65% $88,100
                                                                                70 613.00 598.00 65% 29% 61% $86,381
                                                                                71 405.00 408.00 39% 97% 68% $42,661
                                                                                72 399.00 397.00 31% 87% 47% $32,708
                                                                                73 528.00 514.00 29% 42% 62% $90,849
                                                                                74 433.00 435.00 29% 84% 79% $44,065
                                                                                75 459.00 457.00 28% 85% 72% $50,421
                                                                                76 514.00 509.00 27% 38% 64% $61,332
                                                                                77 502.00 492.00 26% 18% 75% $62,372
                                                                                78 594.00 578.00 56% 26% 39% $134,400
                                                                                79 550.00 551.00 57% 32% 74% $40,909
                                                                                80 534.00 527.00 39% 39% 65% $49,877
                                                                                81 491.00 483.00 27% 57% 72% $63,030
                                                                                82 496.00 491.00 29% 21% 75% $53,465
                                                                                83 500.00 490.00 19% 26% 71% $49,335
                                                                                Total 512.00 502.00 32% 43% 65% $70,231

                                                                                  Filter by high school segments


                                                                                  2011 D+ ClusterSAT MathSAT CRGoing Out of StatePercent NonWhiteNeed Financial AidMed Income
                                                                                  51 462.00 457.00 14% 33% 68% $40,918
                                                                                  52 489.00 496.00 81% 99% 77% $64,730
                                                                                  53 471.00 484.00 28% 38% 62% $60,833
                                                                                  54 376.00 371.00 33% 96% 38% $38,146
                                                                                  55 489.00 481.00 39% 46% 44% $71,845
                                                                                  56 536.00 508.00 73% 43% 49% $63,967
                                                                                  57 434.00 435.00 29% 82% 79% $48,301
                                                                                  58 592.00 577.00 51% 27% 32% $104,509
                                                                                  59 499.00 489.00 19% 18% 74% $47,685
                                                                                  60 523.00 549.00 23% 30% 33% $70,175
                                                                                  61 485.00 370.00 33% 89% 9% $61,385
                                                                                  62 474.00 473.00 34% 92% 67% $55,515
                                                                                  63 440.00 427.00 28% 86% 72% $49,238
                                                                                  64 606.00 542.00 37% 89% 57% $81,911
                                                                                  65 515.00 503.00 28% 43% 65% $72,692
                                                                                  66 498.00 515.00 37% 37% 73% $60,272
                                                                                  67 526.00 546.00 48% 41% 69% $71,279
                                                                                  68 541.00 540.00 41% 26% 62% $79,260
                                                                                  69 390.00 395.00 36% 92% 74% $43,391
                                                                                  70 595.00 581.00 56% 33% 48% $105,721
                                                                                  71 400.00 412.00 57% 98% 80% $43,137
                                                                                  72 528.00 544.00 35% 25% 64% $70,018
                                                                                  73 451.00 438.00 24% 89% 76% $48,406
                                                                                  74 654.00 579.00 76% 80% 46% $59,089
                                                                                  75 514.00 502.00 31% 20% 71% $72,850
                                                                                  76 600.00 584.00 72% 50% 28% $90,265
                                                                                  77 595.00 508.00 64% 75% 39% $39,490
                                                                                  78 473.00 468.00 48% 43% 22% $56,703
                                                                                  79 594.00 585.00 61% 26% 71% $65,180
                                                                                  Total 514.00 502.00 32% 44% 65% $70,223

                                                                                    Segment filter prospects by metro


                                                                                    plot of chunk uiuc-deep-dive

                                                                                      Segment filter prospects interactive map


                                                                                        Women in STEM


                                                                                        Women in STEM prospects by metro

                                                                                        plot of chunk ucsd-deep-dive

                                                                                          Targeting URM students


                                                                                          Race and ethnicity variables, aggregated vs. alone

                                                                                          plot of chunk poc-race-deep-dive

                                                                                            Purchased profiles for students of color by metro


                                                                                            plot of chunk poc-prospects-deep-dive

                                                                                              Purchased profiles for students of color interactive map


                                                                                                Zip code & test score filters


                                                                                                Los Angeles prospects from top income decile zip codes

                                                                                                plot of chunk asu-la-deep-dive

                                                                                                  Discussion


                                                                                                    Data as capital, obfuscation, and policy research


                                                                                                    Student list data derived from user-data of students laboring on platforms

                                                                                                    • Marx (1978): formula for economic capital is \(M - C - M'\)
                                                                                                      • money ($M$); commodities ($C$)
                                                                                                    • Data as capital (Sadowski, 2019)
                                                                                                      • Data an input into production commodities (e.g., software predicting hospital staff needs)
                                                                                                      • Data are a commodity extracted from labor of people using digital platforms
                                                                                                    • College Board follows \(M - C - M'-C-M''\): Invest money ($M$) to develop tests ($C$); sold to households ($M’$) yielding student list data ($C$); sold to universities ($M’’$)
                                                                                                    • Emerging trend: wrap student list data within a software-as-service recruiting product

                                                                                                    Obfuscation (Cottom, 2020; Pasquale, 2015)
                                                                                                    • Opacity of digital platforms is deliberate strategy to manage regulatory environments
                                                                                                    • Really hard to collect data about student list products or “student success” products

                                                                                                    Policy
                                                                                                    • Policy should regulate products sold to schools, universities, and students
                                                                                                    • Developing regulations requires on a body of research
                                                                                                    • Education researchers must interrogate third-party products and vendors
                                                                                                      • Focus on structural inequality embedded in product design

                                                                                                      References


                                                                                                       

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                                                                                                        Appendix


                                                                                                          RQ1


                                                                                                          Test Thresholds

                                                                                                          GPA

                                                                                                          Enrollment Funnel
                                                                                                          P2GPA_inc
                                                                                                          P2GPA_exc

                                                                                                            RQ2


                                                                                                              Academic filters


                                                                                                              GPA filter used

                                                                                                              plot of chunk orders-gpa

                                                                                                                SAT filter used


                                                                                                                plot of chunk orders-sat

                                                                                                                  PSAT filter used


                                                                                                                  plot of chunk orders-psat

                                                                                                                    Geographic filters


                                                                                                                    State filter used by research universities, out-of-state

                                                                                                                    plot of chunk orders-state-research-outofstate

                                                                                                                      State filter used by research universities, in-state


                                                                                                                      plot of chunk orders-state-research-instate

                                                                                                                        Demographic filters


                                                                                                                        Race filter

                                                                                                                        plot of chunk orders-race